Analyzing documents faster and better

STRUCTURED FINANCE 2.0 – A NEW WORKFLOW APPROACH

Structured finance needs to be restructured. The aftermath of the financial crisis has included a broad decline in securitization activity. This is partially explained by the previous excesses in the areas of subprime mortgages, CDOs, and SIVs. New regulatory requirements have further damped securitization activity, producing unintended consequences in the real economy. While an onslaught of new regulations attempted to rein back the excesses, the market displayed a limited ability to self-correct. Following the global financial crisis, asset quality improved and deal structures got simpler.

Despite the trend toward simpler deal structures, documentation for structured financings remains lengthy and complex in most deals. Indeed, the complexity and volume of documents underlying structured finance deals has been a running joke.

This overhead, combined with the velocity of deals in the run up to the crisis, made it difficult (in some cases impossible) for investors and other market participants to absorb the content of important deal documents. In essence, the prevailing method of document analysis of structured finance deals suffered from three primary inefficiencies:

● Document Overload: Structured finance deals had a large number of documents that had to be analysed in-depth and over a short timeframe.

● Overlapping Roles: Front office, middle office and back office analysts across rating agencies, fund management and banking perform similar roles such as extracting information and putting it in word documents, spreadsheets or databases.

● Uncaptured Know-How: Extracting, refining and sharing the deal documentations’ descriptive and subjective information still has to be entered multiple times in investment/risk memos, cash flow models and databases. If doing so is too laborious it is not stored at all or not in an accessible way.

These inefficiencies potentially affect all market participants, including originators, bankers, rating agencies and investors and can result in longer deal times, reduced profitability, and even inability to execute deals altogether.

Post-crisis responses

U.S. lawmakers spotted the issue of lengthy and complex documentation and they partly addressed it with Section 943 of the Dodd-Frank Act. That provision calls for rating agencies to publish reports on the representations and warranties in each deal that they rate (see SEC Rule 17g‑7). However, representations and warranties remain an area of contention, in spite of the rating agency reports. Moreover, representations and warranties account for just a small part of the documentation for a typical deal.

Other post-crisis regulatory changes aim to simplify structures, standardised collateral, and reduce the complexity of transactions. Still others have sought to improve disclosure or to align issuer and investors incentives. Ironically, some of the new regulatory requirements actually amplify the amount of information with which market participants must wrestle during the transaction process. The cost of wrangling information even threatens the economic viability of securitization in certain sectors.

Document analysis

A Document Analysis Platform (“DAP”) offers a method of mitigating document overload. A workflow process using a DAP and the enhanced documents (“Deep Documents”) that it hosts, can create and capture large volumes of information. This can both speed up the transaction process and reduce costs – yielding potentially transformational changes for the securitization market. DAPs and Deep Documents have the potential to achieve what regulations alone cannot notably: (i) improvement in how market participants glean information from transaction documents, (ii) improvement in how they share information from transaction documents, and (iii) improvement in how they understand transaction terms and structures. These benefits can be enjoyed by all transaction participants including bankers, issuers, lawyers, rating agencies, and (last, but certainly not least) investors.

A DAP provides a system for capturing key items of information in a document and tagging the items in ways that make them accessible to users of the document. The information can be captured either automatically or manually, depending on the level of complexity. It can range from “what are the strong points of the deal?” to “what is the ISIN number?” or “what are the latest defaults in the portfolio?” The key is that once the information is captured and tagged, users of the document can handle it more quickly and can apply automation to relate it to similar documents in other deals.

Using a DAP allows for extracting document “data points” in a systematic and automated way. It can empower participants in structured finance transactions by helping them to quickly extract, analyze and process key content from deal documents with less effort. Therefore, it can help revive certain securitization sectors that have languished since the financial crisis.

Conclusion

Reviving the right parts of the structured finance landscape is possible and a good thing. The current information requirements throughout the origination, structuring and investment process have proven to be very inefficient and overly burdensome.

On an individual and at firm level, using a DAP, such as TagDox, can dramatically ease the speed of document review and improve the level and quality of information flow. At an industry level, this can provide a more transparent market, which is something originators, counterparties, investors and regulators have been looking to accomplish.

Structured deal data in DAPs can mitigate the challenge of complexity. It can re-instil confidence in the structured finance market and, over time, make for a fundamentally more liquid and functional market.

Mark Adelson is the editor of the Journal of Structured Finance, former chief credit officer of Standard & Poor’s and former head of structured finance research at Nomura

Eli Luzac is the CEO and founder of TagDox, the world’s first Document Analysis Platform that enables firms and individuals to analyse documents in a collaborative, semi-automated and structured manner.